A synthesis of soil respiration in semi-arid and arid ecosystems across multiple spatial and temporal scales

Principal Investigators:

Mariah S. Carbone

Soil respiration (SR) represents a huge uncertainty in global climate models. This is because we lack a mechanistic understanding of the plant and microbial processes that drive SR rates across different landscapes and in time. Predicting SR in semi-arid/arid ecosystems is particularly challenging because of high interannual variability in precipitation, rapid wetting and drying cycles, large temperature variations, and short phenological cycles. By conducting a multiple phase synthesis of existing continuous SR datasets that span a range of semi-arid/arid... more

Soil respiration (SR) represents a huge uncertainty in global climate models. This is because we lack a mechanistic understanding of the plant and microbial processes that drive SR rates across different landscapes and in time. Predicting SR in semi-arid/arid ecosystems is particularly challenging because of high interannual variability in precipitation, rapid wetting and drying cycles, large temperature variations, and short phenological cycles. By conducting a multiple phase synthesis of existing continuous SR datasets that span a range of semi-arid/arid ecosystem types, this work will improve our basic understanding of the mechanistic controls on SR in these ecosystems. Semi-arid/arid ecosystems cover large areas of Earth, and compared to tropical, temperate and boreal ecosystems, information about them is currently lacking in global synthesis studies. Specifically, this research will identify key biotic and abiotic drivers of SR in these ecosystems, and quantify their relative importance in a clear spatial and temporal framework. This will be accomplished through a combination of basic statistical and time series data analyses, novel isotopic techniques, as well as innovative model-data integration approaches. Results will be used to: (1) improve parameterization and mechanistic representation of SR in models; (2) develop protocols and strategies for quantifying SR in and across semi-arid/arid ecosystems; (3) create a uniform and publically accessible SR database with original and derived data products, including characterization of data uncertainties; and (4) contribute more broadly to a global SR synthesis effort.
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